A Novel Index Supporting High Volume Data Warehouse Insertion
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Chris Jermaine,
Anindya Datta, and
Edward Omiecinski
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While the desire to support fast, ad hoc query processing for large data warehouses has motivated the recent introduction of many new indexing structures, with a few notable exceptions (namely, the LSM-Tree [4] and the Stepped Merge Method [1]) little attention has been given to developing new indexing schemes that allow fast insertions. Since additions to a large warehouse may number in the millions per day, indices that require a disk seek (or even a significant fraction of a seek) per insertion are not acceptable.
In this paper, we offer an alternative to the B+-tree called the
Y-tree
for indexing huge warehouses having frequent insertions. The Y-tree is a new indexing structure supporting both point and range queries over a single attribute, with retrieval performance comparable to the B+-tree. For processing insertions, however, the Y-tree may exhibit a speedup of 100 times over batched insertions into a B+-tree.
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Referenced by
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H. V. Jagadish
: Review - A Novel Index Supporting High Volume Data Warehouse Insertion.
ACM SIGMOD Digital Review 1
: (1999)
@inproceedings{DBLP:conf/vldb/JermaineDO99,
author = {Chris Jermaine and
Anindya Datta and
Edward Omiecinski},
editor = {Malcolm P. Atkinson and
Maria E. Orlowska and
Patrick Valduriez and
Stanley B. Zdonik and
Michael L. Brodie},
title = {A Novel Index Supporting High Volume Data Warehouse Insertion},
booktitle = {VLDB'99, Proceedings of 25th International Conference on Very
Large Data Bases, September 7-10, 1999, Edinburgh, Scotland,
UK},
publisher = {Morgan Kaufmann},
year = {1999},
isbn = {1-55860-615-5},
pages = {235-246},
crossref = {DBLP:conf/vldb/99},
bibsource = {DBLP, http://dblp.uni-trier.de} } },
Copyright(C) 2000 ACM
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